1. Field of the Invention
The present invention relates to image processing devices, image processing methods, image processing programs, and integrated circuits, and in particular relates to image processing devices, image processing methods, image processing programs, and integrated circuits that perform grayscale conversion without enhancing noise in the input signal.
2. Description of the Related Art
In general, image-capturing devices and display devices perform grayscale conversion for the purpose of correcting the brightness or the contrast of an input signal. Pixel unit processing and processing in which the surrounding region is referenced are known as examples of grayscale conversion.
Pixel unit processing is conversion processing that is performed based on only the pixel value of a target pixel, without referencing pixels other than the target pixel. A specific example is gamma correction, which is adopted for captured images in order to cancel out the photoelectric conversion characteristics of CRT display devices.
On the other hand, processing in which the surrounding region is referenced is conversion processing that is performed in reference to not only the pixel value of a target pixel but also to the pixel values of the region surrounding the target pixel or the pixel values of the entire image. A specific example is histogram equalization, in which the distribution of the frequency with which pixel values appear in an input signal is found, and grayscale conversion is performed on the input signal by assigning a wide range of grayscale to frequently appearing grayscale levels in the input image (with histogram equalization, if there is a narrow range of grayscale values that appear frequently in the input signal (for example, a case in which there are 5 to 20 grayscale values in the case of 8-bit data grayscale values), then grayscale conversion is performed to obtain grayscale values over a wide range (for example, 10 to 120 grayscale values) in the output signal). Another specific example is visual processing, in which conversion processing is performed based on the pixel value of the target pixel and the mean value of the pixel values of the surrounding region (mean pixel value).
By applying these grayscale conversions to an input signal, it is possible to obtain a converted signal in which the perception (feeling) of the brightness or the contrast is improved. However, as in the case of gamma correction, when a pixel with a small pixel value is processed with a high gain, the very tiny noise component in the input signal is amplified and the S/N ratio is significantly getting worse. One technology for remedying this issue that has been disclosed is the technology of performing noise reduction processing on the converted signals for pixels with a small pixel value (for example, JP 2001-309177A). With this technology, noise reduction is performed only on pixels in which the slope of the gamma curve, which expresses the input/output characteristics of the grayscale conversion, is greater than a predetermined threshold. As in gamma correction, in cases where the input/output characteristics of the grayscale conversion are determined in advance, those input/output characteristics have monotonically increasing properties, and the slope of the input/output characteristics curve expressing those input/output characteristics has the property of monotonically decreasing, the gain increases the lower the level of the input signal (the level of the input signal with a small grayscale value). Thus pixels in which the S/N ratio becomes poor, that is, pixels with a small pixel value that are processed with a high gain, are specified by detecting input signals that are below the threshold value. By performing noise reduction on the pixels that have been specified in this way, it is possible to improve the deterioration of the S/N ratio in dark areas.
However, with processing in which the surrounding region is referenced, such as histogram equalization and visual processing, the input/output characteristics of the grayscale conversion are changed for each image, or for each pixel, according to the frequency distribution of the pixel values or the mean pixel values around the target pixel of the input signal. When a conventional approach such as gamma correction is adopted in a processing method in which the surrounding region is referenced, it is not possible to pre-calculate the pixel values in which the slope of the input/output characteristics of the grayscale conversion is smaller than a predetermined threshold value, and thus if this is adopted for moving pictures, it is necessary to search the input/output characteristics of the grayscale conversion that are obtained each frame (or each field) or each pixel, and calculate a pixel level (pixel value) of the input signal that corresponds to the threshold value of the slope of the input/output characteristics curve for grayscale conversion that has been obtained. This processing, however, requires a large amount of computations.
In general grayscale conversion, there is no guarantee that the slope of the input/output characteristics curve for the input/output characteristics will decrease monotonically like with gamma correction, and thus with regard to the standard for determining a pixel value in which the slope is equal to or less than the threshold value, there is a possibility that it may not be possible to uniquely determine the range of the pixel levels (pixel values) of the input signal for which to adopt noise reduction.
Threshold processing simply is processing for switching whether or not to adopt noise reduction for a given pixel, and thus it is not possible to carry out noise reduction at a strength that is suited for each pixel.
It is an object of the invention to provide an image processing device, an image processing method, an image processing program, and an integrated circuit with which it is possible to execute noise reduction at a different strength for each target pixel, in accordance with the degree of the deterioration of the S/N ratio due to the amplification of noise components, not only in the case of grayscale conversion where only the target pixel is referenced, but also in the case of grayscale conversion in which the region around the target pixel is referenced also.